Create App.py

App.py

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+import nltk
+from nltk.tokenize import sent_tokenize
+from language_tool_python import LanguageTool
+
+nltk.download('punkt')
+
+def grammar_check(text):
+    tool = LanguageTool('en-US')
+    sentences = sent_tokenize(text)
+    corrected_sentences = []
+    for sentence in sentences:
+        matches = tool.check(sentence)
+        corrected_sentence = tool.correct(sentence)
+        corrected_sentences.append(corrected_sentence)
+    corrected_text = ' '.join(corrected_sentences)
+    return corrected_text
+
+nltk.download('vader_lexicon')
+
+import nltk
+from nltk.sentiment import SentimentIntensityAnalyzer
+
+def analyze_sentiment(text):
+    sia = SentimentIntensityAnalyzer()
+    sentiment_scores = sia.polarity_scores(text)
+    
+    # Positive sentiment: score > 0
+    # Neutral sentiment: score = 0
+    # Negative sentiment: score < 0
+    sentiment = ""
+    if sentiment_scores['compound'] > 0:
+        sentiment = "Positive"
+    elif sentiment_scores['compound'] == 0:
+        sentiment = "Neutral"
+    else:
+        sentiment = "Negative"
+    
+    return sentiment
+
+def count_words(text):
+    words = text.split()
+    total_words = len(words)
+    return total_words
+
+def CsharpGrammarly(text):
+  result1= grammar_check(text)
+  sentiment_result= analyze_sentiment(result1)
+  total_words= count_words(result1)
+  return result1,sentiment_result,total_words
+
+import gradio as gr
+iface = gr.Interface(
+    fn=CsharpGrammarly,
+    inputs=gr.inputs.Textbox(placeholder="Enter your text here..."),
+    outputs=[
+        gr.outputs.Textbox(label="Modified Grammar"),
+        gr.outputs.Textbox(label="Sentiment Analysis"),
+        gr.outputs.Textbox(label="Total Words Count")
+    ],
+    title="CSharpGrammarly",
+    description="Correct spelling, grammar, and analyze sentiment."
+)
+
+iface.launch()